Hello fellow Kagglers:
\n\nNOTE: Posted on behalf of contest co-organizer Dr. Jeff Haberl, Texas A&M.
\n\nPlease find below a collection of technical papers that were generated as part of the ASHRAE Great Predictor Shootout I and II data competitions.
\n\nWhile software stacks, technology and hardware availability have advanced significantly since this time period, the fundamentals of analysis approaches are, still quite fundamental.
\n\nhttps://www.dropbox.com/sh/yk9rvcef7fikv01/AADPt09uCWXc9VM0CFUaIsrNa?dl=0
\n\nA special thanks to Dr. Jeff Haberl for working closely with ASHRAE to release the copyright protections of these works, for this contest.
\n\nGood Luck!
\n\n_Chris
", "messages": [ { "id": 657044, "postDate": "2019-10-24T21:37:09.687Z", "content": "Hello fellow Kagglers:
\n\nNOTE: Posted on behalf of contest co-organizer Dr. Jeff Haberl, Texas A&M.
\n\nPlease find below a collection of technical papers that were generated as part of the ASHRAE Great Predictor Shootout I and II data competitions.
\n\nWhile software stacks, technology and hardware availability have advanced significantly since this time period, the fundamentals of analysis approaches are, still quite fundamental.
\n\nhttps://www.dropbox.com/sh/yk9rvcef7fikv01/AADPt09uCWXc9VM0CFUaIsrNa?dl=0
\n\nA special thanks to Dr. Jeff Haberl for working closely with ASHRAE to release the copyright protections of these works, for this contest.
\n\nGood Luck!
\n\n_Chris
", "rawMarkdown": "Hello fellow Kagglers:\n\n*NOTE: Posted on behalf of contest co-organizer Dr. Jeff Haberl, Texas A&M.* \n\nPlease find below a collection of technical papers that were generated as part of the ASHRAE Great Predictor Shootout I and II data competitions. \n\nWhile software stacks, technology and hardware availability have advanced significantly since this time period, the fundamentals of analysis approaches are, still quite fundamental. \n\nhttps://www.dropbox.com/sh/yk9rvcef7fikv01/AADPt09uCWXc9VM0CFUaIsrNa?dl=0\n\nA special thanks to Dr. Jeff Haberl for working closely with ASHRAE to release the copyright protections of these works, for this contest. \n\nGood Luck!\n\n\n_Chris", "votes": 35 }, { "id": 661507, "postDate": "2019-10-30T12:11:48.073Z", "content": "I am unable to open the link - did you guys succeed?
", "rawMarkdown": "I am unable to open the link - did you guys succeed?\n", "votes": 1, "replies": [ { "id": 664392, "postDate": "2019-11-03T16:00:47.460Z", "content": "Yes. I can. Someone has posted those on github as well:
\n\nhttps://github.com/grapestone5321/Great_Energy_Predictor_Shootout_1_2/tree/master/papers
", "rawMarkdown": "Yes. I can. Someone has posted those on github as well:\n\nhttps://github.com/grapestone5321/Great_Energy_Predictor_Shootout_1_2/tree/master/papers", "votes": 5 }, { "id": 666305, "postDate": "2019-11-06T01:23:50.913Z", "content": "Yes. I've posted those: \nhttps://www.kaggle.com/c/ashrae-energy-prediction/discussion/113136#latest-656881
", "rawMarkdown": "Yes. I've posted those: \nhttps://www.kaggle.com/c/ashrae-energy-prediction/discussion/113136#latest-656881", "votes": 3 } ] }, { "id": 659256, "postDate": "2019-10-27T11:03:35.300Z", "content": "@claytonmiller @chrisbalbach This is super helpful.
\n\nThere are bunch of papers referenced in \"More Buildings Make More Generalizable Models— Benchmarking Prediction Methods on Open Electrical Meter Data\". All most all these papers are behind paywall. Is there any way to access those as well?
", "rawMarkdown": "@claytonmiller @chrisbalbach This is super helpful. \n\nThere are bunch of papers referenced in \"More Buildings Make More Generalizable Models— Benchmarking Prediction Methods on Open Electrical Meter Data\". All most all these papers are behind paywall. Is there any way to access those as well? ", "votes": 1, "replies": [ { "id": 717333, "postDate": "2020-01-13T03:28:39.387Z", "content": "Hey @arnabbiswas1 - I wish I could share all publications that are behind paywalls easily, but its legally problematic. I hope you were able to get access to some of them. Sometimes you can reach out to authors directly on ResearchGate. I know this response comes too late, but future discussion board users may find it useful.
", "rawMarkdown": "Hey @arnabbiswas1 - I wish I could share all publications that are behind paywalls easily, but its legally problematic. I hope you were able to get access to some of them. Sometimes you can reach out to authors directly on ResearchGate. I know this response comes too late, but future discussion board users may find it useful.", "votes": 3 } ] }, { "id": 658737, "postDate": "2019-10-26T13:10:34.800Z", "content": "Maybe this post could be stickied? Edit: thank you!
", "rawMarkdown": "Maybe this post could be stickied? Edit: thank you!", "votes": 1 }, { "id": 700525, "postDate": "2019-12-22T06:33:46.493Z", "content": "sie this is my first python data science project, i am not able to understand the formate of submission file sir i got error
", "rawMarkdown": "sie this is my first python data science project, i am not able to understand the formate of submission file sir i got error " }, { "id": 664260, "postDate": "2019-11-03T12:13:38.640Z", "content": "Thanks for sharing... love it dropbox pdf publications
", "rawMarkdown": "Thanks for sharing... love it dropbox pdf publications" }, { "id": 842741, "postDate": "2020-05-11T16:01:13.463Z", "rawMarkdown": "", "isDeleted": true }, { "id": 660097, "postDate": "2019-10-28T17:14:08.503Z", "content": "Thank you!
", "rawMarkdown": "Thank you!" }, { "id": 660070, "postDate": "2019-10-28T16:18:50.137Z", "content": "Thanks!
", "rawMarkdown": "Thanks!" } ], "comments": [ { "id": 661507, "author_name": "Konrad Banachewicz", "author_url": "", "post_date": "2019-10-30T12:11:48.073000", "content": "I am unable to open the link - did you guys succeed?
", "votes": 1, "replies": [ { "id": 664392, "author_name": "arnab", "author_url": "", "post_date": "2019-11-03T16:00:47.460000", "content": "Yes. I can. Someone has posted those on github as well:
\n\nhttps://github.com/grapestone5321/Great_Energy_Predictor_Shootout_1_2/tree/master/papers
", "votes": 5, "replies": [] }, { "id": 666305, "author_name": "Naruhiko Nakanishi", "author_url": "", "post_date": "2019-11-06T01:23:50.913000", "content": "Yes. I've posted those: \nhttps://www.kaggle.com/c/ashrae-energy-prediction/discussion/113136#latest-656881
", "votes": 3, "replies": [] } ] }, { "id": 659256, "author_name": "arnab", "author_url": "", "post_date": "2019-10-27T11:03:35.300000", "content": "@claytonmiller @chrisbalbach This is super helpful.
\n\nThere are bunch of papers referenced in \"More Buildings Make More Generalizable Models— Benchmarking Prediction Methods on Open Electrical Meter Data\". All most all these papers are behind paywall. Is there any way to access those as well?
", "votes": 1, "replies": [ { "id": 717333, "author_name": "Clayton Miller", "author_url": "", "post_date": "2020-01-13T03:28:39.387000", "content": "Hey @arnabbiswas1 - I wish I could share all publications that are behind paywalls easily, but its legally problematic. I hope you were able to get access to some of them. Sometimes you can reach out to authors directly on ResearchGate. I know this response comes too late, but future discussion board users may find it useful.
", "votes": 3, "replies": [] } ] }, { "id": 658737, "author_name": "S D", "author_url": "", "post_date": "2019-10-26T13:10:34.800000", "content": "Maybe this post could be stickied? Edit: thank you!
", "votes": 1, "replies": [] }, { "id": 700525, "author_name": "Amit", "author_url": "", "post_date": "2019-12-22T06:33:46.493000", "content": "sie this is my first python data science project, i am not able to understand the formate of submission file sir i got error
", "votes": 0, "replies": [] }, { "id": 664260, "author_name": "Patrick Uzuwe", "author_url": "", "post_date": "2019-11-03T12:13:38.640000", "content": "Thanks for sharing... love it dropbox pdf publications
", "votes": 0, "replies": [] }, { "id": 842741, "author_name": "", "author_url": "", "post_date": "2020-05-11T16:01:13.463000", "content": "", "votes": 0, "replies": [] }, { "id": 660097, "author_name": "AJ Aberdein", "author_url": "", "post_date": "2019-10-28T17:14:08.503000", "content": "Thank you!
", "votes": 0, "replies": [] }, { "id": 660070, "author_name": "Ivan Kondratov", "author_url": "", "post_date": "2019-10-28T16:18:50.137000", "content": "Thanks!
", "votes": 0, "replies": [] } ], "raw_markdown_by_id": { "657044": "Hello fellow Kagglers:\n\n*NOTE: Posted on behalf of contest co-organizer Dr. Jeff Haberl, Texas A&M.* \n\nPlease find below a collection of technical papers that were generated as part of the ASHRAE Great Predictor Shootout I and II data competitions. \n\nWhile software stacks, technology and hardware availability have advanced significantly since this time period, the fundamentals of analysis approaches are, still quite fundamental. \n\nhttps://www.dropbox.com/sh/yk9rvcef7fikv01/AADPt09uCWXc9VM0CFUaIsrNa?dl=0\n\nA special thanks to Dr. Jeff Haberl for working closely with ASHRAE to release the copyright protections of these works, for this contest. \n\nGood Luck!\n\n\n_Chris", "661507": "I am unable to open the link - did you guys succeed?\n", "659256": "@claytonmiller @chrisbalbach This is super helpful. \n\nThere are bunch of papers referenced in \"More Buildings Make More Generalizable Models— Benchmarking Prediction Methods on Open Electrical Meter Data\". All most all these papers are behind paywall. Is there any way to access those as well? ", "658737": "Maybe this post could be stickied? Edit: thank you!", "700525": "sie this is my first python data science project, i am not able to understand the formate of submission file sir i got error ", "664260": "Thanks for sharing... love it dropbox pdf publications", "842741": "", "660097": "Thank you!", "660070": "Thanks!" } }